{"id":"W2045967366","doi":"10.1371/journal.pone.0041283","title":"Metagenomic Annotation Networks: Construction and Applications","year":2012,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metagenomics; Annotation; Computer science; Hierarchical organization; Data science; Variety (cybernetics); Computational biology; Biology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003328321,0.001070835,0.0005803448,0.006502295,0.001093943,0.002557386,0.001584736,0.0007267292,0.003176684],"category_scores_gemma":[0.01382965,0.0008669576,0.0009113564,0.007019519,0.0005918586,0.002620118,0.002344465,0.001365445,0.001099797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001522017,"about_ca_system_score_gemma":0.001331102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00355235,"about_ca_topic_score_gemma":0.003946301,"domain_scores_codex":[0.998453,0.00054704,0.0001337917,0.0003720285,0.0004345854,0.00005953233],"domain_scores_gemma":[0.9965564,0.001581562,0.0004727364,0.0005841979,0.0006254643,0.0001796289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005289444,0.0002239681,0.02282995,0.001446691,0.0004205196,0.0007888218,0.001414308,0.1356739,0.03382817,0.1441807,0.01325613,0.6454078],"study_design_scores_gemma":[0.0000353802,0.00004830705,0.007870526,0.0003797463,0.0001028265,0.0006031995,0.0004506995,0.7597354,0.02177439,0.1514413,0.0574589,0.0000993713],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01371765,0.0005922515,0.9731821,0.0005174906,0.00005199588,0.000187597,0.004204176,0.005023725,0.002523011],"genre_scores_gemma":[0.1005456,0.001265717,0.8874728,0.00008502683,0.000038054,0.0004343069,0.008362544,0.0007063423,0.001089572],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006502295,"threshold_uncertainty_score":0.01760209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501157600094982,"score_gpt":0.2032864267343791,"score_spread":0.1882748507334293,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}